class_docstr: multi-positive targets cross entropy loss.
  
  Args:
      reduction (str, optional): The method to reduce the loss.
          Options are "none", "mean" and "sum". Defaults to "mean".
      loss_weight (float, optional): The weight of loss. Defaults to 1.0.
code: def __init__(self, reduction: str = "mean", loss_weight: float = 1.0):
      super(MultiPosCrossEntropyLoss, self).__init__()
      self.reduction = reduction
      self.loss_weight = loss_weight
  
file_path: mmdetection/mmdet/models/losses/multipos_cross_entropy_loss.py
imports: from typing import Optional
  import torch
  from mmengine.model import BaseModule
  from torch import Tensor
  from mmdet.registry import MODELS
  from .utils import weight_reduce_loss
label_desc: Use image node_id 1 to create a new MultiPosCrossEntropyLoss object from inherited base classes: BaseModule with example: obj = MultiPosCrossEntropyLoss(reduction, loss_weight)